Extraction and Application of Cognitive Related Semantic Relationships

Qinge Wang, Xiaofang Kuang, Weiwei Yan, Juan Yang
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Abstract

Unstructured knowledge extraction is the process of recognizing and storing valuable knowledge from the natural language texts. However, few tools are available to automatically extract knowledge concepts and their relations from the text books, especially for those in Chinese. This paper proposed a method to implement the ‘example of’ and ‘part of’ semantic relations' and their related entities' extracting from the digital textbooks in Chinese. The experimental data shows that the extraction of the both relations and the entities can achieve a rather high accuracy and satisfied results comparing with the previous studies.
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认知相关语义关系的提取与应用
非结构化知识提取是从自然语言文本中识别和存储有价值知识的过程。然而,很少有工具可以自动从教科书中提取知识概念及其关系,特别是中文教科书。本文提出了一种从汉语数字教科书中提取“语义关系的实例”和“语义关系的部分”及其相关实体的方法。实验数据表明,与以往的研究相比,关系和实体的提取都取得了较高的精度和满意的结果。
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